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Difference quotient. In single-variable calculus, the difference quotient is usually the name for the expression. which when taken to the limit as h approaches 0 gives the derivative of the function f. [1][2][3][4] The name of the expression stems from the fact that it is the quotient of the difference of values of the function by the ...
Numerical differentiation. Finite difference estimation of derivative. In numerical analysis, numerical differentiation algorithms estimate the derivative of a mathematical function or function subroutine using values of the function and perhaps other knowledge about the function.
A finite difference is a mathematical expression of the form f (x + b) − f (x + a).If a finite difference is divided by b − a, one gets a difference quotient.The approximation of derivatives by finite differences plays a central role in finite difference methods for the numerical solution of differential equations, especially boundary value problems.
Calculus. In calculus, the quotient rule is a method of finding the derivative of a function that is the ratio of two differentiable functions. [1][2][3] Let , where both f and g are differentiable and The quotient rule states that the derivative of h(x) is. It is provable in many ways by using other derivative rules.
In mathematics, the symmetric derivative is an operation generalizing the ordinary derivative. The expression under the limit is sometimes called the symmetric difference quotient. [ 3 ][ 4 ] A function is said to be symmetrically differentiable at a point x if its symmetric derivative exists at that point.
In functional analysis, the functional derivative defines the derivative with respect to a function of a functional on a space of functions. This is an extension of the directional derivative to an infinite dimensional vector space. An important case is the variational derivative in the calculus of variations.
t. e. In calculus, the chain rule is a formula that expresses the derivative of the composition of two differentiable functions f and g in terms of the derivatives of f and g. More precisely, if is the function such that for every x, then the chain rule is, in Lagrange's notation, or, equivalently, The chain rule may also be expressed in ...
Arbitrary stencil points. For arbitrary stencil points and any derivative of order up to one less than the number of stencil points, the finite difference coefficients can be obtained by solving the linear equations [6] where is the Kronecker delta, equal to one if , and zero otherwise. Example, for , order of differentiation :